In manufacturing, for example, in semiconductor device fabrication, product quality is measured directly using metrology tools and indirectly by monitoring the process equipment sensors. This information is collected at different times in the product manufacturing lifecycle and stored in separate, disconnected databases from different vendors. When a manufacturing engineer needs to identify a problem with a process tool or a resulting product, he or she has to go through a laborious and costly process. For example, when an engineer is notified of a potential problem with a product, the engineer has to review corresponding metrology data to find an alarming characteristic of the product, and write down information about the product such as a lot ID, wafer ID, recipe name, etc. The engineer then has to launch another application, manually input the information about the product and search through time series sensor data to find a process tool that was used to manufacture the product. Similarly, when an engineer starts a fault detection evaluation with an alarming characteristic of a process tool, the engineer is faced with an inefficient and error-prone process.